EVALUATION OF CORPORATE SOCIAL PERFORMANCE BASED …msed.vse.cz/msed_2015/article/146-Stankova-Stepanka-paper.pdf · EVALUATION OF CORPORATE SOCIAL PERFORMANCE BASED ON AHP/ANP APPROACH

The9th International DaysofStatistics and Economics, Prague, September10-12, 2015

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EVALUATION OF CORPORATE SOCIAL PERFORMANCE BASED ON AHP/ANP APPROACH

Štěpánka Staňková

Abstract

Generally, the Corporate Social Responsibility concept could be understood as a voluntary

commitment of various organizations to follow principles of an overallsustainability and

a social engagement. Nowadays, an exact measurement is a very questionable and difficult

task, however, it is considered to be crucial for managerial decision making and a following

company development, as well. Another possibility to assess CSR performance of a selected

sample of organizations is connected with a usage of multiple-attribute decision- making

methods (MADM methods) together with a content analysis of existing CSR reports, internet

presentations and CSR publications monitoring CSR approaches of chosen organizations. The

main goal of this paper is connected with the application of the Analytic Hierarchy Process

method (AHP) and Analytic Network Process (ANP) in a complex CSR assessment of

selected banking organizations operating in the Czech Republic.Both methods brought the

same ranking of the organizations within the sample. Českáspořitelna, a.s. achieved the best

scores and it was considered to be the most successful bank. Komerčníbanka, a.s. took

a second place and UniCreditbank Czech Republic, a.s.was placed in the third position.

Key words:Corporate Social Responsibility, Analytic Hierarchy Process (AHP), Analytic

Network Process (ANP), Multiple-Attribute Decision Making, Banking sector

JEL Code:M14, L21

Introduction In 1953 the American economist Howard R. Bowen (Putnová and Seknička, 2007)

introduced his book named Social Responsibilities of Businessman that served as a source of

inspiration for the title of the special study named Corporate Social Responsibility (in short

CSR). Due to a spontaneous development of the CSR study integrating a plenty of scientific

disciplines and expert opinions, a diverse terminology relating to various measurement

methods causes difficulties connected with different interpretations of CSR results and

performance. The main goal of this paper is focused on the evaluation of CSR activities in


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selected banking organizationsbased onthe AHP/ANP methods. A theoretic part of this paper

is focused on more detailed characteristic of the CSR concept and contemporary possibilities

of CSR measurement. The AHP and ANPmethod are described in methodological section,

followed by results and conclusions.

1 Theoretical Basis of Corporate Social Responsibility The stockholder theory (1970) by Milton Friedman together with Richard Edward Freeman´s

stakeholder theory (1984) represents foundations of the CSR concept that, in fact, polarize

opinions of these issues (Putnová and Seknička, 2007).According to Kunz (2012) a long-term

orientation, a systematic approach and voluntariness together with unlimited possibilities of

a practical application are considered to be characteristic features of the CSR definitions.

Contemporary authors such as Coombs and Holladay (2012), Horrigan (2010), Seuring (2012)

and Uyan-Atay (2013) are familiar with a triple-bottom-line concept presented also by the

European Union that includes three basic areas of interest: Profit, Planet and People.

A responsible organization conducts business transparently, respects Corporate Governance

rules, ethical marketing policies and ethical codes, pays attention to quality, innovations or

safety and is universally beneficial to its community (Profit). An environmentally sustainable

organization uses environment-friendly technologies, supports their development and reduces

its environmental impacts (Planet). A responsible organization also fully respects human

rights, occupational health standards and is fair in relation to its stakeholders (People).

2 Research Methodology The main benefits of MADM methods are seen in a systematic decomposition of a complex

decision-making tasks into smaller parts that enables decision makers to express explicitly

(not intuitively) their opinions on criterion importance (preference). Thus the whole process

of decision making becomes transparent, easy to understand and clear for other stakeholders

more or less involved in decision-making procedures (Franek and Zmeškal, 2013).

2.1 Analytic Hierarchy Process

The AHP method was first introduced by its author Thomas L. Saaty at the beginning of

1970s. This MADM method is based on a decomposition of a decision-making problem

forming a top-down structure called a hierarchy and pair-wise comparisons. It is assumed that

each component of a hierarchy is independent(i.e. there are no relations and loops among


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components). The first level of a hierarchy is usually represented by a clear specification of

decision-making goals or tasks. The second level is connected with a formulation of criteria

influencing a final decision while the third layer includes sub-criteria giving accuracy to every

criteria belonging to the previous level. Finally, the fourth level symbolizes a list of

considered options between which decision-making processes are realized (Saaty, 2000).

Before a beginning of pairwise comparisons appropriate number of Saaty´s matrices

(symbolically markedS) corresponding with a hierarchic structure has to be prepared. The

Saaty´s matrix has as many rows and columns as there is the amount of components (criteria,

sub-criteria and options) of each hierarchical level. The judgements are written in the matrix

answering the question: How much more important is one component on the left side of the

matrix in comparison with another at the top of the matrix with respect to its impact on the

level above? When components in rows are preferred to those in columns, then a numerical

expression of magnitudes ranges between ⟨1;9⟩. Value 1 corresponds with an equal

importance (indifference), number 3 means “moderately more”, number 5 “strongly more”,

number 7 “very strongly more” and number 9 “extremely more”. The values 2, 4, 6 and 8 are

used to express a compromise or an intermediate stage of the ratio scale. In the opposite case

estimated magnitudes are expressed on an inverse scale ranging between⟨1 2 ; 19⟩. The

matrix is reciprocal which means that its elements, marked si,j, which are symmetric with

respect to the diagonal, are inverses of one another, 푠 , = 1/푠 , . Moreover, the elements on

the diagonal express equality and are assigned to the value 1 (Saaty, 2000; Zmeškal 2012).

Once all paired comparisons on every hierarchical level are made a computation of

normalized local weights wi, representing a contribution to the parent node in the level

immediately above, follows. Local weights wicould be calculated for example using

geometric mean of rows of Saaty´s matrix S according to a mathematic formula (1), where N

represents the order of Saaty´s matrix S with elements si,j.

N

i

N

N

N

ii

ii

N

jji

N

jji

s

s

vvw

,

,

1

1

. (1)

A requirement of meeting the transitivity condition resulting in the demanded

consistency of Saaty´s matrices is necessary to obtain a high-quality evaluation and reliable


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results. To assess the consistency an eigenvalue 휆 must be computed with respect to

a mathematic procedure given below:

i

N

ii wwS

N /1max , (2)

whereN is the order of Saaty´s matrix S, w symbolizes an eigenvector of weights wi

and (푆 ∙ 푤) stands fori-th element of vector w. A next step is connected with a calculation of

the Consistency Index (CI) and Consistency Ratio (CR) according to a formula:

RIN

N

RICICR 1

max

, (3)

while the Random Index (RI) is determined empirically depending on the order of

Saaty´s matrix S and ranging values mentioned in Table 1. The value of Consistency Index

must definitely meet a condition: 퐶푅 ≤ 0,1.

Tab. 1: Summary of RI values N 1 2 3 4 5 6 7 8 9 10

RI 0,00 0,00 0,58 0,90 1,12 1,24 1,32 1,41 1,45 1,49

Source: Zmeškal (2012)

To obtain the global importance of each sub-criterion considering the overall goal

(Wij), the local weights of criterion wi are multiplied by the local weights of the j-th sub-

criterion according to its effect on the i-th criterion:

jiiji wwW ,, . (4)

The AHP method is based on a principle of utility maximization that is why the option

with the highest sum of the global weights is chosen. This approach is called a distributive

mode synthesis (Saaty, 2000; Álvarez, Moreno and Mataix, 2012).

2.2 Analytic Network Process

Saaty and Vargas (2006) describe the ANP method as a tool for solving decision-making

tasks that cannot be structured hierarchically because they include interactions and mutual

relationships among the elements of a decision-making network. Basically, the ANP is an

extension of the AHP method and it is suitable for a more complex and systematic


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analysis.The network structure does not have the linear form of a hierarchy with strictly

defined levels. By contrast, elements are grouped in components(clusters) that form a system

with relationships, inner and outer dependencies or loops. Currently, the ANP is applied in

various decision-making problems. Especially in the field of CSR the ANP approach was

applied for example by Shiue and Lin (2012) or Hsu, Hu, Chiou and Chen (2011). Once a decision-making task is structured, a procedure of pair-wise comparisons,

importance (preference) appraisals and priority vectors computations is similar to the AHP

(see Chapter 2.1). The only difference is that the elements of each component are compared

pair-wise according to their importance towards their control criterion. The components are

assessed with respect to their contribution to a goal. In a case of interdependencies among

elements (components), a set of pair-wise comparisons need to be carried out to measure the

influence among the elements (components). The results of pair-wise comparisons are written

in Saaty´s matrices.

In the next step, calculated local priority weights (wi,j) derived from all possible and

logical pair-wise comparisons are entered in an appropriate position within an overall matrix,

known as an initialsupermatrix. A standard initialsupermatrix is organized as follows:

11 1

21

1 2

2

( 1) ,

... ......

... ......

n

ij

n n

n

n n n n

W WgoalW W Wcriteria

Wsub criteria

W W W Walternatives

, i=1,…,n; j=1,…, n (5)

To find a convergent solution it is necessary to transform an initial supermatrix into

a weighted supermatrix푊. Finally, a weighted supermatrix푊is used for a computation of

a limit supermatrix푊 according to a formula:

푊 = lim→

푊 , (6)

wherek is an arbitrarily large number (for further details, seeFranek and Zmeškal,

2013, Shiue and Lin, 2012).

3 Utilization of AHP and ANP in Corporate Social Responsibility Concerning the AHP method first of all, it was necessary to create a hierarchic network with

respect to a main goal that is connected with the evaluation of CSR activities of three selected

organizations operating in the Czech banking sector. Each criterion was chosen according to

the triple-bottom-line definition of CSR (see Chapter 1) while it was specified by three sub-


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criteria. It is assumed that every responsible organization fully respects law regulations and

that is why the sub-criteria mainly focus on above-standard commitments and activities. The

graphic representation of the hierarchic structure together with the indication of criteria, sub-

criteria and options (organizations) is shown in Figure 1.

Fig. 1: Hierarchic decomposition of decision-making task

Source: own adaptation according to the CSR definition (Horrigan, 2010)

In second step, the importance (preference) appraisal of criteria and sub-criteria was

accomplished by an expert. Thirdly, local and global weights of criteria and sub-criteria were

calculated. Fourthly, a CSR evaluation of chosen companies was accomplished. A CSR

performance of the three banking organizations was appraised by author´s opinions based on

information got from a content analysis of current internet presentations, CSR reports and

other available publications and surveys. Českáspořitelna, a.s. is marked with the expression

“Organization A”, Komerčníbanka, a.s. is called “Organization B” and finally UniCreditbank

Czech Republic, a.s. is labelled “Organization C”. According to the results of the Czech Top

100 Most Admired Firms survey held in 2014, all of these organizations are considered to be

an essential part of the Czech banking sector.

As for the ANP method, a network was designed (see Figure 2) respecting the same

goal. It is assumed that there are loops in each cluster (i.e. it means inner dependence between

groups of elements).In second step, the importance (preference) appraisal of components and

elements was accomplished by an expert. Thirdly,a CSR evaluation of chosen companies was


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accomplished. Fourthly, an initial supermatrix was computed and through a mathematical

procedure described in Chapter 2.2 a convergent solution was obtained.

Fig. 2: Network structure of decision-making task

Source: own adaptation according to the CSR definition (Horrigan, 2010)

4 Results According to Table 2, obtained priority weights represent a starting point for a complex CSR

performance evaluation. Based on the results of both methods the CSR fields were ordered

identically. In view of the fact that the selected organizations represent the Czech banking

sector the economic field (C1) was rated to be the most preferred criterion. As for AHP

method, the economic field scored 67 % in comparison with 42 % computed by the ANP

approach.Moreover, the social field (C2) and the environmental criterion (C3) were

considered to be more important according to the ANP method. It is obvious that assessed

importance of the CSR fields tends to be more equally distributed according to the ANP than

AHP procedure. Concerning priority weights of CSR sub-criteria, the economic criterion

(C11) connected with an overall safety which means responsible investment, an observance of

occupational health and safety standards, fair behaviour of managers and staff etc. was

assessed as the most important one. It was followed by the criterion (C13) dealing with

various ethical codes and (C31) focused on employee welfare. According to scores of both

methods, only the criteria C12 (Transparent reporting), C22 (Recycling) and C32 (Corporate


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donations) were ordered differently. The criteria C21 (Eco innovations), C32 (Employee

volunteering) and C33 (Eco management and certifications) were the less preferred factors.

Tab. 2: AHP/ANP Comparison of computed priority weights

Field AHP ANP Sub-criterion AHP ANP

Economic field

67,38 % 41,79 %

Safety 36,36 % 18,10 %

Transparent reporting 11,01 % 8,47 %

Ethical codes 20,01 % 16,17 %

Environmental field

10,07 % 22,39 %

Eco innovations 3,13 % 8,11 %

Recycling 4,97 % 9,59 %

Eco management and certifications 1,97 % 4,03 %

Social field

22,55 % 35,82 %

Employee welfare 14,10 % 15,82 %

Corporate donations 5,38 % 12,18 %

Employee volunteering 3,08 % 7,53 %

Source: own computations

The final results required for the complex assessment of the CSR approaches of the

selected banks were obtained using a distributive mode synthesis described in Chapter 2.1.

A detailed overview ofcomputed priority weights is given in Table 3.Based on the results of

both methods the organizations were ordered identically and their scores were nearly the

same.Českáspořitelna, a.s. (Organization A) was considered to be the most successful firm

from the sample (AHP: 53 %, ANP: 51 %). Komerčníbanka, a.s. (Organization B) scored

31 % according to results of AHP and 33 % according to ANP method. Based on the AHP

and ANP outcomes UniCreditbank Czech Republic, a.s. (Organization C) accomplished

nearly 16 %.

Tab. 3: AHP/ANP Comparison of computed priority weights

Field AHP ANP

Organization A

Českáspořitelna, a.s. 53,54 % 51,26 %

Organization B

Komerčníbanka, a.s. 30,65 % 32,97 %

Organization C

UniCreditbank Czech Republic, a.s. 15,82 % 15,77 %

Source: own computations


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Conclusion The main goal of this paper is connected with the evaluation of CSR activities in the selected

banking organizations based on the AHP method and compared with the ANP approach.

Nowadays, various methods such as external audits, certifications, quality marks,

sustainability indices or non-financial reporting initiatives could be appropriately used for

a systematic CSR assessment but they differ in a complexity and are focused on specific areas

where the special requirements have to be met. A solution of multiple-criteria decision-

making tasks based on hierarchical or network decompositions and paired comparisons should

be a helpful managerial toolfor decision making or benchmarking and bring reliable sources

for suitable CSR evaluation procedures.

The application of the AHP/ANP methods in CSR evaluation topics is demonstrated

on a sample consisted of the three organizations: Českáspořitelna, a.s. (Organization A),

Komerčníbanka, a.s. (Organization B) and UniCreditbank Czech Republic, a.s. (Organization

C).Preferences of the criteria and the sub-criteria included in that MADM task were appraised

by an expert, while the CSR performance of each banking organization was considered by the

author´s opinionsbased on information got from a content analysis of current internet

presentations, CSR reports and other available publications and surveys. According to the

results of both methods, the CSR fields and organizations were ordered similarly. As for the

order of sub-criteria, only minor differences were found out. Concerning preferences

distribution the most significant variation was observed within the CSR sub-criteria.

According to the AHP/ANP distributive mode synthesis,Českáspořitelna, a.s., representing

a firm promoting a successful responsible approach, achieved the best results within the

sample. Komerčníbanka, a.s. took a second place and it was followed by UniCreditbank

Czech Republic, a.s.Although the priority weights computed using the AHP and ANP

methods were very similar, there is still an opportunity to explore the relations and

interconnections among the CSR components. In that case a group of experts should be asked

to participate.

Acknowledgment This paper is supported by Student Grant Competition of the Faculty of Economics, VŠB –

Technical University of Ostrava (project registration number: SP2015/93 “Application of

Hybrid MADM Methods in the Field of Business Administration, Management and

Marketing”). All support is greatly acknowledged and appreciated.


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References

Álvarez, M., Moreno, A., &Mataix, C. (2012). The analytic hierarchy process to support decision-making processes in infrastructure projects with social impact. Total Quality Management & Business Excellence, 24(5-6), 596-606. Coombs, W., & Holladay, S. (2012). Managing corporate social responsibility: communication approach. Malden, MA: Wiley-Blackwell. Franek, J. &Zmeškal, Z. (2013).A Model of Strategic Decision Making Using Decomposition SWOT-ANP Method.Financial Management of Firms and Financial Institutions: 9th International Scientific Conference Proceedings, 172 – 180. Horrigan, B. (2010). Corporate social responsibility in the 21st century: Debates, models and practices across government, law and business. Cheltenham, UK: Edward Elgar.

Hsu, C., Hu, A., Chiou, C., & Chen, T. (2011).Using the FDM and ANP to construct a sustainability balanced scorecard for the semiconductor industry. Expert Systems with Applications, (38), 12891-12899. Kunz, V. (2012). Spolecenska odpovednost firem. Praha, CZ: GradaPublishing.

Putnová, A., & Seknička, P. (2007). Eticke rızenı ve firme: nastroje a metody: eticky a socialnı audit. Praha, CZ: GradaPublishing.

Saaty, T. L. (2000). Fundamentals ofdecisionmaking and proritytheorywiththeanalytic hierarchy process. Pittsburgh, PA: RWS Publications.

Saaty, T., & Vargas, L. (2006). Decision making with the analytic network process economic, political, social and technological applications with benefits, opportunities, costs and risks. New York: Springer. Seuring, S. (2012). A review of modelling approaches for sustainable supply chain management. Decision Support Systems, (54), 1513-1520. Shiue, Y., & Lin, C. (2012).Applying analytic network process to evaluate the optimal recycling strategy in upstream of solar energy industry. Energy and Buildings, (54), 266-277. Uyan-Atay, B. (2013). Corporate community involvement: A visible face of CSR in practice. Surrey, UK: Gower Applied Research. Zmeškal, Z. (2012). Application of decomposition multi-attribute methods AHP and ANP in financial decision-making.Managing and Modelling of Financial Risks, 6th International Scientific Conference Proceedings, 689 - 699.

Contact

Štěpánka Staňková

VŠB – Technical University of Ostrava, Faculty of Economics

Sokolská třída 33, 701 21 Ostrava 1

[email protected]

mailto:[email protected]

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